Prediction and identification of Arabidopsis thaliana microRNAs and their mRNA targets.

ABSTRACT:

Background

A class of eukaryotic non-coding RNAs termed microRNAs (miRNAs) interact with target mRNAs by sequence complementarity to regulate their expression. The low abundance of some miRNAs and their time- and tissue-specific expression patterns make experimental miRNA identification difficult. We present here a computational method for genome-wide prediction of Arabidopsis thaliana microRNAs and their target mRNAs. This method uses characteristic features of known plant miRNAs as criteria to search for miRNAs conserved between Arabidopsis and Oryza sativa. Extensive sequence complementarity between miRNAs and their target mRNAs is used to predict miRNA-regulated Arabidopsis transcripts.

Results

Our prediction covered 63% of known Arabidopsis miRNAs and identified 83 new

SUBMITTER: Wang XJ 

PROVIDER: S-EPMC522872 | biostudies-literature | 2004

REPOSITORIES: biostudies-literature